Year in which the incident took place.The full, official name of the cause of death classified by the NCHS.A broader label for the cause of death.The U.S. state where the data was collected.The total number of deaths reported for a specific cause of death.The death rate per 100,000 people, adjusted per age group for fair comparison.
This is the total summation of all Deaths from 1999 to 2017. We can see
that there are many deaths due to Heart Disease and Cancer. The least
amount of deaths being by suicide.
## `summarise()` has grouped output by 'Cause.Name'. You can override using the
## `.groups` argument.
| Year | Total Deaths |
|---|---|
| 1999 | 1,450,384 |
| 2000 | 1,421,520 |
| 2001 | 1,400,284 |
| 2002 | 1,393,894 |
| 2003 | 1,370,178 |
| 2004 | 1,304,972 |
| 2005 | 1,304,182 |
| 2006 | 1,263,272 |
| 2007 | 1,232,134 |
| 2008 | 1,233,656 |
| 2009 | 1,198,826 |
| 2010 | 1,195,378 |
| 2011 | 1,193,154 |
| 2012 | 1,199,422 |
| 2013 | 1,222,210 |
| 2014 | 1,228,696 |
| 2015 | 1,267,684 |
| 2016 | 1,270,520 |
| 2017 | 1,294,914 |
This plot show how Heart Disease has been decreasing throughout time. The United States started bringing in more awareness to Heart Disease and people started reaching out for help. We can see that from 2010 and 2012, we see a dip in deaths, this is due to the Million Hearts being launched by the United States Department of Health. Their main goal was to prevent 1 million heart diseases by 2017. We can see this dip in the plot above. Before 2010, This can be due to people making better choices for themselves, such as not smoking and better eating habits.
| Year | Total Deaths |
|---|---|
| 1999 | 1,099,676 |
| 2000 | 1,106,182 |
| 2001 | 1,107,536 |
| 2002 | 1,114,542 |
| 2003 | 1,113,804 |
| 2004 | 1,107,776 |
| 2005 | 1,118,624 |
| 2006 | 1,119,776 |
| 2007 | 1,125,750 |
| 2008 | 1,130,938 |
| 2009 | 1,135,256 |
| 2010 | 1,149,486 |
| 2011 | 1,153,382 |
| 2012 | 1,165,246 |
| 2013 | 1,169,762 |
| 2014 | 1,183,400 |
| 2015 | 1,191,860 |
| 2016 | 1,196,076 |
| 2017 | 1,198,216 |
In this data we can see that the deaths caused by cancer keep increasing throughout the years. We can see that there is a dip in 2004, this is due to some states statistical data not meeting the requirements to be included to the US data. Since this happened, the amount of deaths decreased due to some states not meeting the requirements to input their data.
| State | Year | Total Deaths | Known Cause Deaths | Unclassified Deaths |
|---|---|---|---|---|
| Alabama | 2017 | 53,238 | 39,366 | 13,872 |
| Alaska | 2017 | 4,411 | 3,118 | 1,293 |
| Arizona | 2017 | 57,758 | 42,928 | 14,830 |
| Arkansas | 2017 | 32,588 | 25,233 | 7,355 |
| California | 2017 | 268,189 | 206,761 | 61,428 |
| Colorado | 2017 | 38,063 | 27,626 | 10,437 |
| Connecticut | 2017 | 31,312 | 22,103 | 9,209 |
| Delaware | 2017 | 9,178 | 6,902 | 2,276 |
| District of Columbia | 2017 | 4,965 | 3,581 | 1,384 |
| Florida | 2017 | 203,636 | 152,459 | 51,177 |
This plot represents the total amount of deaths through these diseases,
but also the amount of unexplained deaths. The unexplained deaths can be
due to the data being specifically based on the top 10 deaths in the
United States. The total amount of deaths is from all residents death
certificates that were filed through this time.
Different states or regions have different age structures.
Older populations naturally have higher death rates so comparing raw death rates across states would be misleading.
To make fair comparisons across the states, public health stats use age adjustment instead of uing raw numbers.
## Coordinate system already present. Adding new coordinate system, which will
## replace the existing one.
When looking at all these graphs throughout the time, we can see the
amount of deaths and the Age Adjusted Death Rate together. We see that
through many of the death causes like CLRD, Stroke, Diabetes, Influeza
and Pneumonia there has been a decrease throughout time. We see a huge
decrease in the cause stroke also. Strokes can be caused if you have
diabetes, it is an underlining of strokes because it can damage your
blood vessels and cause your blood to cloth. We can see that diabetes
has also decrease. Therefore these two are somewhat reflecting off of
each other to an extent.
When we look at this data, we can notice that there has been a change in Heart Disease and Cancer throughout these years. When I searched it up a bit more, it says that there can be changes throughout the years due to better technology. Due to better technology, these diseases are faster to detect. Therefore the age gap between the amount of deaths is closing in. Creating a greater percentage for those who have an older population. While deaths may be high, this can be due to the population increasing over the time.
## Coordinate system already present. Adding new coordinate system, which will
## replace the existing one.
While presenting we were asked about Florida specifically, mainly about
the age in Florida. We were not given ages, but we can look at the Age
Adjusted Death Rate and see that the percentages have increased.
Alzheimer’s disease is mainly diagnosed on people of older age. (Ages
65+) This disease has had an increase in Florida, so yes we can say that
older people do live in Florida. Before though, not many people. The Age
Adjusted Death Rate didn’t see in increase until 2011, therefore now
there are probably more older people moving to Florida.
##LIMITATION
This project has been very interesting to work on. There are some limitations on it. I think it would’ve been better if our data also included ages. We think this would’ve helped a lot in some of the questions that we were receiving from people. Ages play a big roll into these diseases, we are given a bit by the Age Adjusted Death Rate but not to the fullest (Specifics on age range). I also think that it would’ve been nice to have the specific type of Cancer. We are given a more generalized name for Cancer, it is all in one category instead of being a general Cancer name and a specific Cancer name.